What value of R-squared is considered good?

No value of the R-Squared can be interpreted as good or bad. This statistical tool does not measure the performance of an asset. It only tells you the extent of variation in the asset for any variation in its benchmark.

Is it better if the R-squared is high?

No, a high R-squared value doesn't automatically mean it's "better." It simply tells you how much of a security's price movements are explained by the benchmark's movements.

What does it mean if an asset has an R-squared of 0.5?

An R-Squared value of 0.5 or 50% means that only half the variation in the asset’s price can be traced back to variation in the benchmark. The other half depends on other unexplained factors.

What does a low R2 value indicate?

A low R-Squared value means that only a small part of the extent of variation in the asset can be linked to variation in its benchmark.

What is the meaning of R-squared in mutual funds?

The R-squared in mutual funds indicates how similar or different the performance of the fund is when compared to its benchmark.

What is the R2 of a portfolio?

The R-squared of an investment portfolio measures the extent to which the portfolio varies along with its benchmark. The higher the R-squared value, the more of the portfolio’s variation can be linked to its benchmark.

Why is R-squared value so low?

A low R-squared value for a mutual fund can stem from factors such as active management diverging from the benchmark, unique investment strategies, or a diversified portfolio that deviates significantly from the benchmark's composition.

What is a good R-squared for a mutual fund?

A good R-squared for a mutual fund depends on its investment objectives. Generally, for index funds aiming to closely track benchmarks, a high R-squared (close to 100%) is favourable. However, for actively managed funds striving to outperform benchmarks, a moderate to lower R-squared may indicate effective diversification and independent performance.

How do you interpret the R-squared?

Interpreting the R-squared involves assessing the degree to which a mutual fund's movements correlate with its benchmark. A higher R-squared implies stronger correlation, suggesting that changes in the benchmark significantly influence the fund's performance. Conversely, a lower R-squared indicates less dependency on the benchmark, potentially reflecting active management strategies or unique portfolio allocations.

What does an R-squared value of 0.3 mean?

An R-squared value of 0.3 indicates a moderate level of correlation between a mutual fund and its benchmark. Roughly 30% of the fund's movements can be explained by changes in the benchmark. This suggests some influence of the benchmark on the fund's performance but also indicates significant divergence, which may result from active management or unique investment strategies.

Can I choose mutual funds with a low R-squared value?

Yes, you can choose mutual funds with a low R-squared value. A low R-squared indicates that the fund's performance is not closely correlated with the benchmark index, which can be desirable if you seek diversification and want to reduce market-specific risks.

What does R-squared measure?

R-squared measures how well your data fits a regression model. It tells you how much of the variation in the outcome (dependent variable) can be explained by the factors you are studying (independent variables). For example, if the R-squared is 0.7, it means that 70% of the changes in the outcome are explained by your model, while the remaining 30% are due to other factors not included in the model.

What is the range of R-squared values?

R-squared values range from 0 to 1. A value of 0 means the independent variables don't explain any of the variation in the outcome. On the other hand, a value of 1 means the model perfectly explains all the variations in the outcome. Hence, we can also say that values closer to 1 indicate a “better fit”, while values closer to 0 indicate a “poorer fit”.

Why might the R-squared value be misleading?

R-squared value can be misleading if a model is overfitted. This means it includes too many variables that don’t really help explain the outcome. In such a situation, even if R-squared is high, the model might not predict future results accurately. That’s because the model fits the current data too closely and does not perform well with new or unseen data. Moreover, in such cases, the model appears accurate for the data it was trained on, but it usually does not accurately capture the true patterns or predict future outcomes.

How can I improve the R-squared of a model?

To improve R-squared, you can focus on including only the most relevant predictors that genuinely impact the outcome. Also, you can address “multicollinearity”. For those unaware, it represents a situation where two or more predictors (independent variables) in a model are too similar or highly correlated. You can address this problem by using techniques like variance inflation factor analysis. Lastly, you can refine your model by exploring different variable relationships (such as non-linear or interaction terms) to better capture the patterns in the data.

What does the R2 value tell you?

The R-squared value is a statistical metric that quantifies the proportion of variance in the dependent variable that is explained by the independent variables in a regression model. R-squared values range from 0 to 1. A value of 0 indicates that the model explains none of the variation in the dependent variable, while a value of 1 signifies that the model perfectly predicts the dependent variable.

What does an R2 value of 0.9 mean?

A model with an R-squared value of 0.9 demonstrates that 90% of the variance in the dependent variable can be attributed to the independent variables. This signifies a robust association between the variables and suggests that the model effectively describes the relationship within the data.

Is a R2 value of 0.8 good?

An R-squared value of 0.8 generally indicates a strong relationship between the variables in a regression model. It suggests that 80% of the variance in the dependent variable can be explained by the independent variable(s). Think of it like a score: Excellent: R-squared > 0.9 Good: R-squared > 0.8 Fair: R-squared > 0.7 Poor: R-squared < 0.7

Can R2 be greater than 1?

No, the R-squared value cannot be greater than 1. An R-squared of 1 indicates a perfect fit, where the model explains 100% of the variance in the data. If the model perfectly predicts the data, there is no residual error. When there is any residual error, meaning the model doesn't perfectly fit the data, the R-squared will be less than 1.

R-Squared - Meaning, Formula and Calculation

R Squared

R-Squared (R²), or the coefficient of determination, quantifies the proportion of variance in the dependent variable explained by the independent variable in a regression model. It reflects how effectively the data align with the regression model's predictions.

3 min

20-August-2025

Ever looked at a mutual fund’s performance chart and wondered how much of its ups and downs are just following the market? That’s where R-Squared steps in. For many investors, especially beginners, understanding how much a fund mirrors its benchmark index can be confusing. But knowing this can help you choose the right fund for your strategy—whether you're looking for something that sticks closely to the market or one that takes its own path.

If you’ve ever asked, “Is this fund actually doing well, or is it just riding the wave?”, R-Squared is the answer you’ve been searching for. In this guide, let’s break down what R-Squared means, how it works, and how to actually use it in your mutual fund decisions—without the complex maths. Understanding metrics like R-Squared can help you spot which funds genuinely outperform and which just follow the tide. Compare mutual fund schemes instantly.

What is R-Squared?

R-Squared, often written as R², tells you how closely a mutual fund’s returns match its benchmark index. In simpler terms, it measures how much of a fund's performance can be explained by movements in the overall market.

Imagine a fund that's tracking the Nifty 50. If its R-Squared is 100%, that means every movement in the fund mirrors the index exactly. On the other hand, if the R-Squared is 0%, it’s behaving totally independently. Most mutual funds will fall somewhere in between.

So why does this matter? Because it tells you how “active” or “passive” the fund really is. If you’re investing in an actively managed fund, you’d want it to beat the index, not just follow it. A very high R-Squared might mean the fund isn’t adding much extra value beyond what the market’s already doing.

The closer a fund sticks to the market, the more important it becomes to question whether active management is worth the cost. Explore top-performing mutual funds

How does R-Squared work?

Let’s simplify this with a quick example. Suppose you're evaluating two equity mutual funds—Fund A and Fund B—both benchmarked against the Nifty 50.

Fund A has an R-Squared of 95%. That means 95% of its movements are explained by the Nifty 50. It’s closely tracking the index.

Fund B has an R-Squared of 65%. This fund is behaving quite differently from the Nifty 50. It may be taking more active bets, investing in mid-caps or sectoral themes, or simply following a very different strategy.

The higher the R-Squared, the more “market-like” the fund is. The lower it is, the more independently the fund moves. This can be both good or bad—it depends on what kind of investment approach you're looking for.

R-Squared is particularly helpful when used with other indicators like alpha and beta. For instance, a high alpha only means something if R-Squared is high too. Otherwise, that outperformance may not be related to the benchmark at all.

Pairing R-Squared with other ratios helps you dig deeper into the real drivers of fund performance. Open your mutual fund account today

R-Squared formula and calculating the value

While you don’t need to crunch the numbers yourself—most mutual fund factsheets or platforms provide the R-Squared value—it’s still good to know what’s behind the scenes.

The formula for R-Squared is:

R² = (Correlation between Fund and Benchmark)² × 100

Let’s break that down:

First, we find the correlation between the fund’s returns and the benchmark index’s returns. This value lies between -1 and 1.

Then we square it, which ensures the value lies between 0 and 1.

Finally, we multiply by 100 to express it as a percentage.

So, if a fund has a correlation of 0.90 with its benchmark, the R-Squared would be:

R² = (0.90)² × 100 = 81%

This means 81% of the fund’s returns can be attributed to movements in the benchmark. The rest—19%—is due to other factors like fund manager decisions, sector allocation, or timing strategies.

Knowing the formula helps decode whether your fund’s gains are skill-driven or just market mimicry. Start SIP with just Rs. 100

How is R-Squared different from correlation?

It's easy to confuse R-Squared with correlation because both deal with the relationship between a mutual fund and its benchmark. But they serve different purposes.

Correlation tells you the direction of the relationship—whether the fund moves in the same direction as the benchmark or in the opposite direction. R-Squared, however, tells you the strength of that relationship—how much of the fund’s performance is actually explained by the benchmark’s movements.

For example, a fund could have a correlation of +0.9 with its benchmark, meaning it generally moves in the same direction. But if its R-Squared is only 40%, that means only 40% of the fund’s performance is actually driven by the benchmark. The remaining 60% comes from other factors.

Why R-Squared matters in mutual fund investing

R-Squared is especially useful when you’re assessing active vs. passive funds. Suppose you're paying a high management fee for an actively managed fund. You’d expect that fund to outperform its benchmark by making smart, independent investment decisions.

But what if that fund has an R-Squared of 98%? That suggests it’s not straying much from the benchmark. In that case, you might question whether the high fee is justified.

On the flip side, a low R-Squared doesn’t automatically mean better or worse—it just means the fund is doing something different. Whether that’s good or bad depends on the fund manager’s skill and your investment goal.

Using R-Squared to evaluate fund manager performance

If you're trying to assess whether a fund manager is truly adding value, R-Squared can help. A high alpha looks great—but only if the fund also has a high R-Squared. That shows the outperformance is in comparison to the benchmark, not just random returns.

For example, if a fund shows 3% alpha but has an R-Squared of only 50%, that alpha may not be meaningful. It may be coming from factors outside the benchmark’s scope.

On the other hand, a fund with 3% alpha and 90% R-Squared is more reliable—it’s beating the market while still being benchmark-aligned.

When is R-squared useful for investors?

R-Squared can be incredibly helpful when you're choosing between actively and passively managed funds. Let’s say you’re evaluating an actively managed equity fund. If it has an R-Squared of 98%, it’s closely tracking its benchmark—perhaps too closely. That might make you question whether the fund manager is really adding value or just mimicking the index while charging higher fees.

On the flip side, if you’re looking at a passive fund or an index fund, a high R-Squared is a good thing. It tells you the fund is doing its job of closely following the benchmark.

How to interpret R-squared values

Here’s a general way to read R-Squared values in mutual funds:

100% – 95%: The fund closely follows the benchmark. Likely a passive or index fund.
95% – 70%: The fund somewhat tracks the benchmark but may have some active strategy.
Below 70%: The fund has a high degree of independence from its benchmark. Active strategy likely dominates.

These ranges are not hard rules but offer a helpful lens. Also, context matters. A sectoral fund or thematic fund may naturally have a lower R-Squared because it’s focused on a niche area.

By learning how to interpret R-Squared, you gain a valuable filter to assess how aligned a fund is with your investment expectations—especially when building a diversified portfolio. Explore top-performing mutual funds!

What R-squared doesn’t tell you

It’s important to know that R-Squared only tells you how closely a fund tracks its benchmark—it doesn’t say whether the fund is outperforming or underperforming it. That’s where other metrics come into play.

Alpha tells you about excess returns.
Beta tells you about volatility.

A fund could have a high R-Squared and still perform poorly. So, don’t judge a fund based on this one number alone. Use it as one of several tools to make informed investment decisions.

Real-world example of R-Squared

Let’s say you’re analysing a mid-cap mutual fund benchmarked against the Nifty Midcap 150 index. Over the last 3 years, the fund shows an R-Squared of 88%. That tells you that 88% of its performance can be explained by the index’s movements. The remaining 12%? That’s where the fund manager’s decisions, sector plays, and allocation strategies come in.

This insight is crucial because many investors assume a fund’s high returns are purely because of its active strategy. But if the R-Squared is very high, a lot of that return may simply be due to the overall market moving up.

How much R-Squared is ideal?

There’s no perfect R-Squared score—what’s “ideal” depends on your investment style. If you prefer index funds or ETFs, a higher R-Squared (90% or above) is actually desirable, because it means your fund is closely following the index.

On the flip side, if you’re paying higher fees for an actively managed fund, you might want a slightly lower R-Squared. Why? Because you expect the fund manager to take independent calls and generate alpha. If R-Squared is too high, it could mean the fund isn’t as “active” as it claims.

You want the score to align with the fund’s stated strategy and your expectations—nothing more, nothing less.

Using R-Squared with other mutual fund metrics

R-Squared isn’t meant to be used in isolation. Pair it with metrics like:

Alpha – If a fund shows a high alpha but low R-Squared, the alpha might not be related to the benchmark at all.
Beta – Tells you about volatility, while R-Squared tells you how well the volatility aligns with the index.
Standard deviation – Explains how scattered the fund returns are.

R-Squared vs. Beta

Both R-Squared and beta are tools that measure a fund's relationship with the market, but they focus on different things. Beta tells you how much a fund moves in response to market movements—essentially the fund’s volatility. R-Squared, on the other hand, tells you how well those movements are explained by the benchmark.

So, a fund could have a high beta (very volatile) but a low R-Squared (not much in sync with the market), or vice versa. Ideally, when you're looking at mutual fund metrics, these two should be read together. For example, if a fund has a high beta and a high R-Squared, it’s both volatile and highly correlated with the index—perhaps not ideal for a conservative investor.

If you’ve ever struggled to understand whether a fund is simply risky or just actively managed, these metrics offer much-needed clarity. Compare mutual fund options now!

Limitations of R-Squared

While R-Squared is useful, it’s not the full story. A high R-Squared doesn't mean the fund is good or bad—it just means it closely follows the benchmark. It doesn't measure returns, risk, or outperformance. A fund can have a high R-Squared but still deliver poor returns.

Another issue is that R-Squared is backward-looking. It’s based on historical data, and past correlations may not hold in the future—especially in volatile markets or during economic shifts. It also doesn’t account for sector or thematic deviations that may be strategic in nature.

Key takeaways

R-Squared shows how much of a mutual fund’s performance is explained by its benchmark index.
A high R-Squared (close to 100%) means the fund is closely tracking its benchmark.
A low R-Squared suggests the fund is moving independently and possibly making active bets.
It’s best used alongside other metrics like alpha and beta to get a full picture.
R-Squared does not measure quality, returns, or future performance. It’s a correlation metric, not a rating.

Conclusion

R-Squared might seem like just another complex statistic, but when broken down, it’s one of the most useful tools for investors trying to judge how “market-like” a mutual fund is. Whether you want a fund that hugs the index or one that breaks away from it, this metric offers a peek into how a fund really behaves.

Use it with other indicators, and you’ll get a sharper, clearer view of your mutual fund's DNA. At the end of the day, investing is part science, part art—and tools like R-Squared help you balance both. Making sense of metrics like R-Squared can be the difference between blind investing and smart investing. Start investing or SIP with just Rs. 100!

After you have performed the required analysis and identified the funds you want to invest in, you can visit the Bajaj Finserv Mutual Funds Platform and start your lump sum or SIP investment. With over 1,000 funds available to choose from, you are bound to find the funds that align with your risk preferences and financial goals.